The decoder of NAO[1]}, which is similar to the decoder in the DNN model, the decoder in NAO is responsible for decoding out the string tokens in \(x\) , taking \(e_{x}\)  as input. Mathematically the decoder is denoted as function \(\mathrm {D}: \mathrm {C} \rightarrow \mathrm {X}\)  which decodes the input taking \(e_{x}\) .
The training process consist of optimizing the following loss : \(\sum _{x \in X} \log P_{D}(x \mid E(x))\) .
